kangar00: Kernel Approaches for Nonlinear Genetic Association Regression
Methods to extract information on pathways, genes and various single-nucleotid polymorphisms (SNPs) from online databases. It provides functions for data preparation and evaluation of genetic influence on a binary outcome using the logistic kernel machine test (LKMT). Three different kernel functions are offered to analyze genotype information in this variance component test: A linear kernel, a size-adjusted kernel and a network-based kernel (Friedrichs et al., 2017, <doi:10.1155/2017/6742763>).
| Version: |
1.4 |
| Depends: |
R (≥ 3.1.0) |
| Imports: |
methods, bigmemory, sqldf, biomaRt, KEGGgraph, CompQuadForm, data.table, lattice, igraph |
| Suggests: |
testthat |
| Published: |
2020-02-17 |
| Author: |
Juliane Manitz [aut], Stefanie Friedrichs [aut], Patricia Burger [aut],
Benjamin Hofner [aut], Ngoc Thuy Ha [aut], Saskia Freytag [ctb],
Heike Bickeboeller [ctb] |
| Maintainer: |
Juliane Manitz <r at manitz.org> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| Citation: |
kangar00 citation info |
| CRAN checks: |
kangar00 results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=kangar00
to link to this page.